Primiparous sow behaviour on the day of farrowing as one of the primary contributors to the growth of piglets in early lactation.

Large White and Meishan sows differ in maternal ability and early piglet growth. We investigated the relationships between 100 maternal traits, grouped into 11 blocks according to the biological function they describe and litter growth over three successive periods after birth (D0-D1, D1-D3 and D3-D7; D0 starting at the onset of farrowing), as a measure of sow investment in early piglet production. Within- and between-breed variation was exploited to cover a maximum of the variability existing in pig maternal populations.

Puzzle: taking livestock tracking to the next level.

Animal behavior is a critical aspect for a better understanding and management of animal health and welfare. The combination of cameras with artificial intelligence holds significant potential, particularly as it eliminates the need to handle animals and allows for the simultaneous measurement of various traits, including activity, space utilization, and inter-individual distance. The primary challenge in using these techniques is dealing with the individualization of data, known as the multiple object tracking problem in computer science.

CherryChèvre: A fine-grained dataset for goat detection in natural environments.

We introduce a new dataset for goat detection that contains 6160 annotated images captured under varying environmental conditions. The dataset is intended for developing machine learning algorithms for goat detection, with applications in precision agriculture, animal welfare, behaviour analysis, and animal husbandry. The annotations were performed by expert in computer vision, ensuring high accuracy and consistency.

Analysis of image-based sow activity patterns reveals several associations with piglet survival and early growth.

An activity pattern describes variations in activities over time. The objectives of this study are to automatically predict sow activity from computer vision over 11 days peripartum and estimate how sow behavior influences piglet's performance during early lactation. The analysis of video images used the convolutional neural network (CNN) YOLO for sow detection and posture classification of 21 Large White and 22 Meishan primiparous sows housed in individual farrowing pens.

A Non-Invasive Millimetre-Wave Radar Sensor for Automated Behavioural Tracking in Precision Farming-Application to Sheep Husbandry.

The automated quantification of the behaviour of freely moving animals is increasingly needed in applied ethology. State-of-the-art approaches often require tags to identify animals, high computational power for data collection and processing, and are sensitive to environmental conditions, which limits their large-scale utilization, for instance in genetic selection programs of animal breeding. Here we introduce a new automated tracking system based on millimetre-wave radars for real time robust and high precision monitoring of untagged animals.

Mixed grazing of adult goats and cattle: Lessons from long-term monitoring.

Mixed grazing of breeding goats and cattle (goats to cattle ratio: about 50 %, based on metabolic weight) was monitored for 2 years on a rotational pasture with the two species grazing together, then for 5 years with cattle grazing immediately after goats. For both modalities, the level of goat parasite infection was not significantly different from that of the control groups. Nevertheless, the association allowed a slight improvement in kid growth and goat productivity, probably in relation to a better food quality.

Goats worm burden variability also results from non-homogeneous larval intake.

For small ruminants, Gastrointestinal Nematodes (GINs) are responsible for severe economic losses and they are also an animal welfare problem. GIN use their host to reproduce and disperse eggs on the pasture, from where they can re-infect another animal. The high density of hosts on the pasture and the extreme tolerance of GIN to environmental constraints make GIN eradication almost impossible.

Dynamic minimum set problem for reserve design: Heuristic solutions for large problems.

Conversion of wild habitats to human dominated landscape is a major cause of biodiversity loss. An approach to mitigate the impact of habitat loss consists of designating reserves where habitat is preserved and managed. Determining the most valuable areas to preserve in a landscape is called the reserve design problem.